Forecasting sales and Developing Budgets Dr Pusanisa Thechatakerng

Forecasting sales and Developing Budgets Dr. Pusanisa Thechatakerng E-mail: drsunnyt@yahoo. com 1

Market Potential and Sales Potential (I) The total expected sales of a given product or service for the entire industry in a specific market over a state of time (total industry concept) Four elements: • The item being marketed (the product, service, idea, person or location) • Sales for the entire industry in dollars or product • A specific time period • A specific market delineated either geographically, by type of customer, or both. 2

Market Potential and Sales Potential (II) Sales potential The maximize share (or percentage) of market potential that an individual firm can reasonably expect to achieve Company’s sales potential – specific the product, market, and time period Ex. Budweiser brand accounted for 40% of the approximately 180 million barrels of beer consumed in the USA in 2004 - Budweiser beer’s sales potential is close to 40% of market in the coming year 3

Market Potential and Sales Potential (III) Sales forecast An estimate of sales (in dollars) that an individual firm expects to achieve during a specified forthcoming time period, in a stated market, under a proposed marketing plan Less than the sales potential for many different reasons Ex. 4 ps < quality, financial problem 4

Estimating Market Potential and Sales Potential (I) 1. Market-factor Derivation – Market factor • An item or element in a market that causes the demand for a product or service or • Related to the demand Ex. Bangkok’s population annual as a market factor underlying the demand for sandal. This element is related to the number of sandal that manufacturer can sell 5

Estimating Market Potential and Sales Potential (II) Market-factor Derivation Ex. Bangkok’s population annual as a market factor underlying the demand for sandal. This element is related to the number of sandal that manufacturer can sell. The sales potential for sandal as follows: Estimate number of Bangkok’s pop = 4, 000 Times: percent who buy sandal = x 0. 33 (33%) Market potential 1, 350, 000 Times: Potential market share Sales potential = x 0. 30 (30%) 396, 000 6

Estimating Market Potential and Sales Potential (III) 2. Surveys of Buyer Intention for determining potential – Consists of contacting potential customer and questioning them about whether or not they would purchase the product or service at the price asked. Ex. The manufacturer established that it would be satisfied if it sold 50, 000 leather sandal pairs per year. Since the cost of the pair would be higher than that of plastic pair. The manufacturer want to know 2 things. First, how many people would buy product at retail price B. 200? Second, What did 7 customers think the price of such a product should be?

Estimating Market Potential and Sales Potential (IV) • Survey through personal interviews with 240 Bkkpop. • 170 of 240 (approximately 71%) were interested in product. • They indicated that price should be B. 130 to capture that size of market • The average (mean) price quoted (B. 145) would eliminate half of respondents who showed interest in the product. • Still 10 people (4% of market) said they would be interested in purchasing the product at retail price B. 200 • Survey showed 1/3 of BKKpop purchase sandal 8

Estimating Market Potential and Sales Potential (V) Estimate number of Bangkok’s pop = 4, 000 Times: percent who buy sandal = Market potential x 0. 33 (33%) 1, 350, 000 Times: taking 4% of the result = x 0. 04 (4%) Market potential for B. 200 leather sandal = 52, 800 pairs >50, 000 = o. k Yes - based on information obtain directly from people No – cost & time 9

Sales Forecasting • Executive opinion Survey methods: • Sales force composite • Buyers’ intentions • Moving average model Mathematical methods • Exponential smoothing models • Regression models Operational method “Must-do” calculations • Capacity-based calculations 10

Source of sales forecast data -Executive opinion Executives & managers Customers -Sales force composite Survey of buyer intention -Moving average models Historical data -Exponential smoothing -Regression analysis Company operation -“Must-do” approach -Capacity-based approached -Test market 11

Moving average method Month Actual sales Total sales (3 months) Forecast sales 1 120 - - 2 130 - - 3 110 360 120. 00 4 140 380 126. 67 5 110 360 120. 00 6 130 380 126. 67 12

Exponential Smoothing Models Month Actual sales Total sales (month/s) Forecast sales 1 x 120 = 120 - 2 x 130 = 260 - 3 (6) x 110 = 330 710 4 118. 33 5 128. 33 6 120. 00 P. S 6/710=118. 33 13

Regression Analysis (sales trends into the future) Sales (millions) 2010 forecast, 10 yrs base 35 30 25 20 15 10 5 2001 02 03 04 05 07 09 10 14

“Must-Do” Forecasts • Reasonable forecast is the sales that must be achieved for the firms to reach its break-even point. • Ex. One new service enterprise budgeted its total overhead costs at $165, 000 for the first year. The entrepreneur desired a profit of $60, 000, which would represent her salary. Thus, she projected sales at $225, 000 for the year and proceeded to plan on that basis 15

Capacity-Based Forecasts • Ex. Restaurant 10 tables, each table for 4 people, only lunch 30 Baht/food with drink, open everyday • So 10 x 4 = 40 seat • 40 x 365 = 438, 000 16

Review the forecasting process (Method) • Use more than one method • Select the right method – Short period • Moving average models • Exponential smoothing models – Long period • Regression models 17

Problems (I( • Indicate what market factor or factors you would use to estimate the market potentials for each of the following products: Mc. Graw-Hill economics textbooks, Chang Beer, 12 plus roll-on, Johnson baby powder, Nike sport shoe, MK Suki. 18

Problems (II( • In, general, how do sales forecast based on surveys differ from forecasts based on mathematic methods? 19

Problems (III( • Tiger company’s monthly sales; Months: January, February, March, April Sales 250 268 320 345 Forecast sales force on May by using moving average method (3, 2, 1) 20

Problems (IV( • Tiger company’s monthly sales; Months: January, February, March Sales 250 268 320 Forecast sales force on April by using exponential smoothing method (3, 2, 1) 21